Datamation content and product recommendations are editorially independent. We may make money when you click on links to our partners. Learn More.
Noted data storage expert Henry Newman points out — in contradiction to other tech analysts — that budgeting for storage requires more than simply extrapolating from today’s costs.
Those of you that read my column regularly know I look at things a little differently than some of the big name industry analysts, such as Gartner or IDC, and try to look at the reasons behind the predictions.Most of the articles I read from these two groups and others talk about budgets in terms of how much total hardware will be sold, and much of that is based on the economy. I see the problem for budgeting much differently. In my view the problem is you need to buy terabytes or petabytes of storage capacity – if you are Google maybe tens of petabytes of – and I believe there are going to be some significant technology changes for disk storage that will, in turn, impact your budgets.
The way I view the problem, is that you will need to buy a defined amount of storage and that has a cost, and too many bean counters, accountants, university researchers and big industry analysts, just draw straight lines based recent history on density and cost. They make the assumption that they have solved the problem and know what the cost will be. The last time I checked, technology growth, for the most part, does not happen on a straight line. The cost per GB for disk technology flattens compared to the old technology cost per GB when it is introduced. The cost quickly gets more dense and lower and then lines flatten again at the end of the technology lifecycle.
Here is a history of Seagate Enterprise disk drives:
Read the rest at Enterprise Storage Forum.
RELATED NEWS AND ANALYSIS
-
Ethics and Artificial Intelligence: Driving Greater Equality
FEATURE | By James Maguire,
December 16, 2020
-
AI vs. Machine Learning vs. Deep Learning
FEATURE | By Cynthia Harvey,
December 11, 2020
-
Huawei’s AI Update: Things Are Moving Faster Than We Think
FEATURE | By Rob Enderle,
December 04, 2020
-
Keeping Machine Learning Algorithms Honest in the ‘Ethics-First’ Era
ARTIFICIAL INTELLIGENCE | By Guest Author,
November 18, 2020
-
Key Trends in Chatbots and RPA
FEATURE | By Guest Author,
November 10, 2020
-
Top 10 AIOps Companies
FEATURE | By Samuel Greengard,
November 05, 2020
-
What is Text Analysis?
ARTIFICIAL INTELLIGENCE | By Guest Author,
November 02, 2020
-
How Intel’s Work With Autonomous Cars Could Redefine General Purpose AI
ARTIFICIAL INTELLIGENCE | By Rob Enderle,
October 29, 2020
-
Dell Technologies World: Weaving Together Human And Machine Interaction For AI And Robotics
ARTIFICIAL INTELLIGENCE | By Rob Enderle,
October 23, 2020
-
The Super Moderator, or How IBM Project Debater Could Save Social Media
FEATURE | By Rob Enderle,
October 16, 2020
-
Top 10 Chatbot Platforms
FEATURE | By Cynthia Harvey,
October 07, 2020
-
Finding a Career Path in AI
ARTIFICIAL INTELLIGENCE | By Guest Author,
October 05, 2020
-
CIOs Discuss the Promise of AI and Data Science
FEATURE | By Guest Author,
September 25, 2020
-
Microsoft Is Building An AI Product That Could Predict The Future
FEATURE | By Rob Enderle,
September 25, 2020
-
Top 10 Machine Learning Companies 2021
FEATURE | By Cynthia Harvey,
September 22, 2020
-
NVIDIA and ARM: Massively Changing The AI Landscape
ARTIFICIAL INTELLIGENCE | By Rob Enderle,
September 18, 2020
-
Continuous Intelligence: Expert Discussion [Video and Podcast]
ARTIFICIAL INTELLIGENCE | By James Maguire,
September 14, 2020
-
Artificial Intelligence: Governance and Ethics [Video]
ARTIFICIAL INTELLIGENCE | By James Maguire,
September 13, 2020
-
IBM Watson At The US Open: Showcasing The Power Of A Mature Enterprise-Class AI
FEATURE | By Rob Enderle,
September 11, 2020
-
Artificial Intelligence: Perception vs. Reality
FEATURE | By James Maguire,
September 09, 2020